The present technology relates to a control device, a control method, and a program that enable the action of a movable body to be planned in accordance with the value of a peripheral object. The control device according to an embodiment of the present technology estimates a value of an object at the periphery of a movable body on the basis of sensor data detected by the movable body, and plans an action of the movable body on the basis of the value of the object estimated. The present technology is applicable to robots capable of acting autonomously.

An information processing system according to an embodiment of the present disclosure includes a first information processing device to be provided to a movable body and a second information processing device to be provided to a portion that differs from the movable body. The first information processing device includes a sensor portion, a generation portion, a control portion, and an integration portion. The sensor portion senses a first external environment. The generation portion uses sensor data acquired from the sensor portion to generate a first map. The control portion controls motion of a manipulator on the basis of the first map. The integration portion uses position information of inside the first external environment, with which portion the manipulator is in contact, integrates the first map and a second map acquired from the second information processing device with each other, and generates an integration map.

An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

The present disclosure provides a flight anti-collision method and apparatus based on electromagnetic field detection of an overhead transmission line. An example method includes: determining whether an overhead transmission line around is an Alternating Current (AC) transmission line or a (Direct Current) DC transmission line; if the overhead transmission line is an AC transmission line, determining a position relationship between an aircraft and the overhead transmission line on the basis of a phase distribution model and an electric field phase and a magnetic field phase measured by a phase detector on the aircraft; if the overhead transmission line around is a DC transmission line, determining the position relationship between the aircraft and the overhead transmission line on the basis of a magnetic field intensity distribution model and the magnetic field intensities collected by magnetic field intensity sensors on the aircraft; and thus controlling the aircraft.

A monitoring method includes identifying a monitoring target and a warning object in space according to data collected by a data collection apparatus, obtaining position information of the monitoring target and the warning object, determining a warning area based on the position information of the monitoring target, and generating warning information based on a position relationship between a position of the warning object and the warning area.

Systems and methods are provided for detecting and responding to cut in vehicles, and for navigating while taking into consideration an altruistic behavior parameter. In one implementation, a navigation system for a host vehicle may include a data interface and at least one processing device. The at least one processing device may be programmed to receive, via the data interface, a plurality of images from at least one image capture device associated with the host vehicle; identify, based on analysis of the plurality of images, at least one target vehicle in an environment of the host vehicle; determine, based on analysis of the plurality of images, one or more situational characteristics associated with the target vehicle; determine a current value associated with an altruistic behavior parameter; and determine based on the one or more situational characteristics associated with the target vehicle that no change in a navigation state of the host vehicle is required, but cause at least one navigational change in the host vehicle based on the current value associated with the altruistic behavior parameter and based on the one or more situational characteristics associated with the target vehicle.

A control system uses visual odometry (VO) data to identify a position of the vehicle while moving along a path next to the row and to detect the vehicle reaching an end of the row. The control system can also use the VO image to turn the vehicle around from a first position at the end of the row to a second position at a start of another row. The control system may detect an end of row based on 3-D image data, VO data, and GNSS data. The control system also may adjust the VO data so the end of row detected from the VO data corresponds with the end of row location identified with the GNSS data.

Systems and methods for enhancing task performance and computer readable maps produced by robots using modular sensors is disclosed herein. According to at least one non-limiting exemplary embodiment, robots may perform a first set of tasks, wherein coupling one or more modular sensors to the robots may configure a robot to perform a second set of tasks, the second set of tasks includes the first set of tasks and at least one additional task.

A method of controlling a movable platform includes obtaining depth information of a scene in a first direction based on a first image captured by a first sensor of the movable platform and a third image by a third sensor of the movable platform, respectively; obtaining depth information of a scene in a second direction based on a second image captured by a second sensor of the movable platform and the third image by the third sensor of the movable platform, respectively; and controlling movement of the movable platform in space based on the depth information of the scene in the first direction and the second direction. The first sensor, the second sensor and the third sensor are mounted on the movable platform at substantially a same level. The third sensor has a first and a second overlapping field of view with the first sensor and the second sensor, respectively.

The method for autonomous vehicle control preferably includes sampling measurements, determining refined sensor poses based on the measurements, determining an updated vehicle pose based on the measurements and operation matrix, optionally determining evaluation sensor poses based on the refined sensor poses, optionally updating the operation matrix(es) based on the evaluation sensor poses, and/or any other suitable elements. The system for autonomous vehicle control can include one or more vehicles, one or more sensors, one or more processing systems, and/or any other suitable components.